6533b85dfe1ef96bd12be62e

RESEARCH PRODUCT

Strategies for accelerating ant colony optimization algorithms on graphical processing units

Alejandro CatalaJose A. MocholiJavier Jaen

subject

Extremal optimizationMathematical optimizationTheoretical computer scienceOptimization problemComputer scienceComputationAnt colony optimization algorithmsArtificial lifeMetaheuristicParallel metaheuristic

description

Ant colony optimization (ACO) is being used to solve many combinatorial problems. However, existing implementations fail to solve large instances of problems effectively. In this paper we propose two ACO implementations that use graphical processing units to support the needed computation. We also provide experimental results by solving several instances of the well-known orienteering problem to show their features, emphasizing the good properties that make these implementations extremely competitive versus parallel approaches.

yearjournalcountryeditionlanguage
2007-09-012007 IEEE Congress on Evolutionary Computation
https://doi.org/10.1109/cec.2007.4424511